fix: 修复 5 项确定 bug + Provider UX 重做 + 文档统一
Bug fixes: - fix(dao): AsyncSession.delete 补齐漏掉的 await（provider/user/individual 共 4 处） - fix(worker): result.data.output → result.output.output（pydantic-ai 1.x API 适配） - fix(api): 删除 create_worker_from_template 死端点（ORM 字段不匹配必崩） - fix(api): /provider/test 按 provider_type 分支适配 Anthropic/Gemini/OpenAI 三种协议 - fix(chat): SSE 流式聊天在 distributed 模式 fallback 到非流式，避免 asyncio.Queue 序列化崩溃 Features (previously unstaged): - feat(provider): Provider 管理页重做（品牌图标、5 种类型、Test Connection、编辑模式） - feat(provider): 新增 Gemini provider_type 支持 - feat(workflow): Finalize 节点输出 blackboard 摘要 + 失败原因；步骤完成/失败实时推送 SSE - feat(i18n): regulatory_node 提示词从路由模式改为直接对话模式（中英双语） - feat(consciousness): dynamic_prompt 支持 locale 国际化 - feat(logs): SystemLogsView 自动刷新 + 暂停按钮 Docs: - docs: README/README-EN 统一为"开源通用多 Agent 协作平台"口径 - docs: ROADMAP 按 v0.1.x / v0.2.x / v0.3.x 重组 - docs: project.md 重写为结构化项目介绍 Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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@@ -39,6 +39,7 @@ class ConsciousnessNode:
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self.logger = get_logger("consciousness_node")
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self.agent: None | Agent = None
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self.locale: str = "zh"
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async def create_agent(
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self,
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@@ -51,6 +52,7 @@ class ConsciousnessNode:
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custom_system_prompt: str | None = None,
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) -> None:
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system_prompt: str = agent_prompt("consciousness_node", locale=locale, custom_system_prompt=custom_system_prompt)
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self.locale = locale or "zh"
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output_type = Union[ForregulatoryNode, ForWorkflow, ForWorkflowEngine]
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from kilostar.core.global_state_machine.gsm_snapshot import fetch_snapshot
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@@ -74,23 +76,43 @@ class ConsciousnessNode:
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@self.agent.system_prompt
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async def dynamic_prompt(ctx: RunContext[ConsciousnessNodeDeps]):
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locale = ctx.deps.locale
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prompt = system_prompt + "\n\n"
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prompt += (
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f"=== 当前任务上下文 ===\n"
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f"- 当前指令 (Command): {ctx.deps.command}\n"
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f"- 原始用户命令 (Original Command): {ctx.deps.original_command}\n"
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)
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if ctx.deps.available_skills:
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prompt += "\n=== 当前可用 Skill Individual ===\n"
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prompt += "你可以直接将以下 Skill Individual 安排进工作流的步骤中（设置 node 为 skill_individual，并将 agent_id 设置为对应 Skill Individual 的真实 agent_id，不要用名称！），作为可调用的工具。\n"
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for skill in ctx.deps.available_skills:
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prompt += f"- 真实 agent_id: {skill.get('agent_id')}\n 名称: {skill['name']}\n 描述: {skill['description']}\n"
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if locale == "en":
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prompt += (
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f"=== Current Task Context ===\n"
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f"- Command: {ctx.deps.command}\n"
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f"- Original User Command: {ctx.deps.original_command}\n"
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)
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if ctx.deps.available_skills:
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prompt += "\n=== Available Skill Individuals ===\n"
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prompt += "You may assign the following Skill Individuals to workflow steps (set node to skill_individual, and set agent_id to the real agent_id below — never use the name!).\n"
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for skill in ctx.deps.available_skills:
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prompt += f"- agent_id: {skill.get('agent_id')}\n Name: {skill['name']}\n Description: {skill['description']}\n"
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else:
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prompt += "\n=== IMPORTANT: No Worker Individuals Available ===\n"
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prompt += "No Worker Individuals are registered. When generating a workflow, you have exactly two options:\n"
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prompt += "1. Assign the step to consciousness_node itself (set node to consciousness_node, agent_id to null).\n"
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prompt += "2. If the task truly requires specialized tools, refuse and explain that a Worker must be created first.\n"
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prompt += "NEVER fabricate non-existent agent_ids!\n"
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else:
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prompt += "\n=== 重要：当前无可用 Worker Individual ===\n"
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prompt += "系统中当前没有注册任何 Worker Individual。在生成工作流时，你有且仅有以下两种选择：\n"
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prompt += "1. 将步骤分配给 consciousness_node 自己完成（设置 node 为 consciousness_node，agent_id 为 null）。\n"
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prompt += "2. 如果任务确实需要专用工具或技能才能完成，则拒绝执行并在输出中说明需要先创建对应的 Worker。\n"
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prompt += "绝对禁止编造不存在的 agent_id！\n"
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prompt += (
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f"=== 当前任务上下文 ===\n"
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f"- 当前指令: {ctx.deps.command}\n"
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f"- 原始用户命令: {ctx.deps.original_command}\n"
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)
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if ctx.deps.available_skills:
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prompt += "\n=== 当前可用 Skill Individual ===\n"
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prompt += "你可以直接将以下 Skill Individual 安排进工作流的步骤中（设置 node 为 skill_individual，并将 agent_id 设置为对应 Skill Individual 的真实 agent_id，不要用名称！）。\n"
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for skill in ctx.deps.available_skills:
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prompt += f"- 真实 agent_id: {skill.get('agent_id')}\n 名称: {skill['name']}\n 描述: {skill['description']}\n"
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else:
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prompt += "\n=== 重要：当前无可用 Worker Individual ===\n"
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prompt += "系统中当前没有注册任何 Worker Individual。在生成工作流时，你有且仅有以下两种选择：\n"
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prompt += "1. 将步骤分配给 consciousness_node 自己完成（设置 node 为 consciousness_node，agent_id 为 null）。\n"
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prompt += "2. 如果任务确实需要专用工具或技能才能完成，则拒绝执行并在输出中说明需要先创建对应的 Worker。\n"
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prompt += "绝对禁止编造不存在的 agent_id！\n"
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return prompt
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@@ -127,7 +149,6 @@ class ConsciousnessNode:
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original_command=command, available_skills=available_skills
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)
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# 通知 SSE 正在生成图结构（pending 队列：节点端写入 → API SSE 读取，单向下行）
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global_workflow_manager = ray_actor_hook(
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"global_workflow_manager"
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).global_workflow_manager
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@@ -135,7 +156,6 @@ class ConsciousnessNode:
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trace_id, "正在为您构建并规划工作流任务节点，请稍候..."
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)
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# 实际构建过程
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result = await self.working(payload)
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if result and isinstance(result, ForWorkflowEngine):
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@@ -197,6 +217,7 @@ class ConsciousnessNode:
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original_command=payload.original_command,
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command="自主分析并拆解原始命令，生成严密可执行的工作流",
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available_skills=payload.available_skills,
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locale=self.locale,
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)
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self.logger.debug("ConsciousnessNode: 开始生成工作流 (原生重试开启)")
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prompt = "根据original_command制定严密的可执行workflow"
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@@ -207,6 +228,7 @@ class ConsciousnessNode:
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deps = ConsciousnessNodeDeps(
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original_command=payload.original_command,
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command="完成workflow step中分配给意识节点的特定任务或指导",
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locale=self.locale,
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)
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self.logger.debug(
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"ConsciousnessNode: 开始处理工作流节点任务 (原生重试开启)"
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@@ -221,6 +243,7 @@ class ConsciousnessNode:
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deps = ConsciousnessNodeDeps(
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original_command=payload.original_command,
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command="对于工作流整体执行结果进行检查，并且生成一份专业的技术性总结报告",
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locale=self.locale,
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)
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self.logger.debug(
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"ConsciousnessNode: 开始生成技术总结报告 (原生重试开启)"
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@@ -28,7 +28,8 @@ class ConsciousnessNodeDeps(DepsModel):
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"""ConsciousnessNode 在 pydantic-ai Agent 中使用的依赖：原始指令、当前指令以及可用 Skill 列表。"""
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original_command: str
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command: str
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available_skills: Optional[List[str]] = None
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available_skills: Optional[List[dict]] = None
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locale: str = "zh"
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class ConsciousnessNodeInput(RequestModel):
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"""ConsciousnessNode 各类入参的共同基类，仅用于打 schema 标签。"""
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@@ -30,10 +30,9 @@ from kilostar.utils.i18n import agent_prompt
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@actor_class
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class RegulatoryNode:
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"""RegulatoryNode（监管节点）：用户请求的入口路由 Actor。
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"""RegulatoryNode（监管节点）：用户请求的直接对话节点。
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负责对消息做意图识别：闲聊 → 直接回 ``ForUser``；复杂任务 → 走
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``ForConsciousnessNode`` 移交给意识节点；工作流回执 → 转译成对用户的总结回复。
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负责理解用户需求并提供回复；如果收到工作流执行报告则转化为用户友好的总结。
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"""
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def __init__(self) -> None:
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@@ -100,12 +99,9 @@ class RegulatoryNode:
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f"- 用户名 (User): {ctx.deps.user_name}\n"
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f"- 当前时间 (Time): {ctx.deps.time}\n"
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)
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# 修改 system_prompt 变量
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prompt += (
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"\n\n注意：你必须调用且只能调用一个函数（工具）来输出结果。"
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"如果你想直接回复用户，请调用 ForUser；"
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"如果你想移交给工作流，请调用 ForConsciousnessNode。"
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"严禁返回纯文本，必须使用工具格式！"
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"\n\n注意：请基于上下文信息为用户提供准确、专业的回复。"
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"如果你有可用工具，可在需要时主动调用。"
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)
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if ctx.deps.error_history:
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prompt += (
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@@ -130,7 +126,7 @@ class RegulatoryNode:
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"规则：\n"
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"1. 直接、详细地回答用户问题，像一个专业且友好的助手。\n"
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"2. 如果你有可用工具，可以调用工具来辅助回答（如搜索、读文件等）。\n"
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"3. 不要输出内部思考过程，不要做路由判断，不要提及 ForUser/ForConsciousnessNode 等格式。\n"
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"3. 不要输出内部思考过程，直接给出回复内容。\n"
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"4. 回复应当完整、有帮助，避免过于简短。\n"
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)
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